Development of TGF-beta antagonists for cancer therapy

开发用于癌症治疗的 TGF-β 拮抗剂

• 批准号: 9153704
• 负责人: Lalage Wakefield
• 金额: $ 87.44万
• 依托单位: DIVISION OF BASIC SCIENCES - NCI
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/9153704
• 关键词: 4T1; Address; Adult; Advanced Malignant Neoplasm; Adverse effects; Antibodies; Biological; Biological Assay; Biological Markers; Biology; Cell Proliferation; Cell Survival; Cells; Cessation of life; Clinical; Clinical Data; Clinical Treatment; Clinical Trials; Complex; DNA Sequence; Data; Detection; Development; Ecosystem; Embryonic Development; Epithelial; Gene Expression Profile; Generations; Goals; Growth Factor; Heterogeneity; Homeostasis; Human; Immune response; Immunologic Surveillance; Knowledge; Ligation; Literature; Maintenance; Malignant Neoplasms; Messenger RNA; Metastatic breast cancer; Methods; Modeling; Molecular; Monitor; Mus; Mutation; Neoplasm Metastasis; Outcome; Pathway interactions; Patients; Pharmacodynamics; Phase; Play; Pre-Clinical Model; Primary Neoplasm; Protein Isoforms; Proteins; Role; Sampling; Signal Transduction; Staging; Technology; Testing; Therapeutic; Therapeutic Uses; Transforming Growth Factor Beta 2; Transforming Growth Factor beta; Transforming Growth Factor-Beta Overexpression; Transgenic Organisms; Tumor Cell Line; Tumor Promoters; Tumor Suppression; Tumor Suppressor Proteins; Work; angiogenesis; base; cancer therapy; carcinogenesis; cell motility; comparative efficacy; exome; genetic regulatory protein; human TGFB1 protein; immune function; improved; in vivo; malignant breast neoplasm; mouse model; neoplastic cell; neutralizing antibody; novel strategies; outcome forecast; pre-clinical; response; therapeutic target; transcriptomics; transforming growth factor beta3; treatment strategy; tumor; tumor microenvironment; tumor progression; tumorigenesis

Despite the dual role for TGF-beta as both tumor suppressor and tumor promoter in carcinogenesis, preclinical data from our lab and others has previously suggested that strategies to antagonize TGF-beta may selectively reduce the undesirable tumor promoting effects of this growth factor while sparing the desirable effects on tumor suppression and normal homeostasis. Based on these promising preclinical results, several different TGF-beta pathway antagonists are in early phase clinical trials for the treatment of advanced cancer. However, given the complex biology of TGF-beta, the successful development of TGF-beta antagonists for cancer therapy will depend on a clear understanding of how these agents work, and the related question of how to select patients who will benefit from this type of treatment. In our previous work, we performed detailed mechanistic analysis of the mode of action of anti-TGF-beta neutralizing antibodies in the widely used 4T1 transplantable mouse model of metastatic breast cancer. Using a panel of 12 transplantable syngeneic mouse models of metastatic breast cancer, with metastatic burden as the primary therapeutic endpoint, we had previously uncovered heterogeneous responses to TGF-beta antagonism, with inhibition of metastasis in some models, and no effect on or stimulation of metastasis in other models. We have applied discovery-based approaches to address molecular and biological mechanisms underlying the heterogeneity of therapeutic response and to generate useful predictive biomarkers. Whole exome DNA sequencing of the tumor cell lines has shown that none of the commonly occurring mutations in breast cancer are correlated with response to therapy. Transcriptomic analysis of untreated primary tumors in the panel segregates tumors by response to anti-TGF-beta therapy, suggesting that the therapeutic response is dictated by prominent, readily identifiable molecular and biological features of the tumor. Tumors from models showing a desirable response to TGF-beta antagonism are characterized by reduced immune function, enhanced angiogenesis, higher tumor cell proliferation and survival, and transcriptomic evidence of TGF-beta pathway activation in the untreated state. Gene expression signatures that are predictive of response to anti-TGF-beta therapy have been generated and are being tested in additional preclinical models. In our search for useful predictive and pharmacodynamic biomarkers of TGF-beta antagonism, we have developed approaches for quantitative and more sophisticated monitoring of TGF-beta pathway activation in tumors, adapting the ProteinSimple SimpleWestern technology for accurate quantitation of Smad activation in tumor samples, and developing a quantitative brightfield proximity ligation assay for detection of the non-canonical "mixed Smad" signaling complexes that are associated with pathological TGF-beta signaling. We have also begun to address whether it might be possible to improve the therapeutic response to TGF-beta antagonism by selective neutralization of different TGF-beta isoforms. Correlative clinical data and literature evidence suggests that whereas TGF-beta1 is primarily associated with poor outcome, TGF-beta3 may actually oppose TGF-beta1 and be associated with good outcome, providing a rationale for selective neutralization of TGF-beta1 and TGF-beta2, while sparing TGF-beta3. As part of this initiative, we have developed methods for accurate quantitation of TGF-betas in tumor extracts since we have shown that TGF-beta mRNA levels do not correlate well with protein levels for TGF-beta1 and TGF-beta3. We have assessed TGF-beta isoform protein levels across the metastatic tumor panel and find that TGF-beta1:TGF-beta3 ratios vary over a 20-fold range. Therapeutic anti-TGF-beta antibodies with different isoform selectivity will be compared for efficacy in representative models. Through this approach, we hope to generate improved TGF-beta-targeted therapeutics.

尽管 TGF-β 在致癌作用中具有肿瘤抑制因子和肿瘤促进因子的双重作用，但我们实验室和其他实验室的临床前数据先前表明，拮抗 TGF-β 的策略可以选择性地减少这种生长因子的不良肿瘤促进作用，同时避免对肿瘤抑制和正常体内平衡具有理想的效果。基于这些有希望的临床前结果，几种不同的 TGF-β 途径拮抗剂正处于治疗晚期癌症的早期临床试验中。然而，鉴于 TGF-β 的复杂生物学特性，用于癌症治疗的 TGF-β 拮抗剂的成功开发将取决于对这些药物如何发挥作用的清晰了解，以及如何选择将从此类药物中受益的患者的相关问题。治疗。在我们之前的工作中，我们对广泛使用的转移性乳腺癌 4T1 可移植小鼠模型中抗 TGF-β 中和抗体的作用模式进行了详细的机制分析。使用一组 12 个可移植的转移性乳腺癌同基因小鼠模型，以转移负担作为主要治疗终点，我们之前发现了对 TGF-β 拮抗剂的异质反应，在一些模型中抑制了转移，并且对 TGF-β 拮抗剂没有影响或刺激其他模型中的转移。我们应用基于发现的方法来解决治疗反应异质性背后的分子和生物机制，并生成有用的预测生物标志物。肿瘤细胞系的全外显子组 DNA 测序表明，乳腺癌中常见的突变均与治疗反应无​​关。该组中未经治疗的原发性肿瘤的转录组分析通过抗TGF-β治疗的反应来分离肿瘤，这表明治疗反应是由肿瘤的突出的、易于识别的分子和生物学特征决定的。来自模型的肿瘤对 TGF-β 拮抗剂表现出理想的反应，其特征是免疫功能降低、血管生成增强、肿瘤细胞增殖和存活率更高，以及在未治疗状态下 TGF-β 途径激活的转录组证据。预测抗 TGF-β 疗法反应的基因表达特征已经产生，并正在其他临床前模型中进行测试。在寻找 TGF-β 拮抗作用的有用预测和药效生物标志物的过程中，我们开发了定量和更复杂地监测肿瘤中 TGF-β 通路激活的方法，采用 ProteinSimple SimpleWestern 技术对肿瘤样本中的 Smad 激活进行准确定量，并开发定量明场邻近连接测定法，用于检测与病理性 TGF-β 信号传导相关的非典型“混合 Smad”信号复合物。我们还开始探讨是否有可能通过选择性中和不同的 TGF-β 异构体来改善对 TGF-β 拮抗作用的治疗反应。相关临床数据和文献证据表明，虽然 TGF-β1 主要与不良预后相关，但 TGF-β3 实际上可能对抗 TGF-β1 并与良好预后相关，这为选择性中和 TGF-β1 和 TGF-β2 提供了理论依据。同时保留 TGF-β3。作为该计划的一部分，我们开发了准确定量肿瘤提取物中 TGF-β 的方法，因为我们已经证明 TGF-β mRNA 水平与 TGF-β1 和 TGF-β3 的蛋白质水平没有很好的相关性。我们评估了转移性肿瘤组中的 TGF-β 同种型蛋白水平，发现 TGF-β1:TGF-β3 比率变化超过 20 倍。将比较具有不同亚型选择性的治疗性抗 TGF-β 抗体在代表性模型中的功效。通过这种方法，我们希望产生改进的 TGF-β 靶向疗法。